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Inferring Intracellular Signal Transduction Circuitry from Molecular Perturbation Experiments

  • Special Issue: Mathematical Oncology
  • Published:
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Abstract

The development of network inference methodologies that accurately predict connectivity in dysregulated pathways may enable the rational selection of patient therapies. Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology. Living cells integrate extremely robust circuits that exhibit significant heterogeneity, but still respond to external stimuli in predictable ways. This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments. The methodology relies on logic-based networks to provide a predictive approximation of the transfer of signals in a network. The approach presented was validated in silico with a set of test networks and applied to investigate the epidermal growth factor receptor signaling of a breast epithelial cell line, MFC10A. In our analysis, we predict the potential signaling circuitry most likely responsible for the experimental readouts of several proteins in the mitogen-activated protein kinase and phosphatidylinositol-3 kinase pathways. The approach can also be used to identify additional necessary perturbation experiments to distinguish between a set of possible candidate networks.

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Acknowledgements

SS and MLW acknowledge support from the James S. McDonnell Foundation’s grant support for studying complex systems. This work was also partially supported by NIH R25 DK088752 (NC and SS), the University of Michigan Protein Folding Diseases Initiative (SS), the Breast Cancer Research Foundation (MLW, ME, ZFW, and SDM), and the Avon Foundation (ZFW and SDM).

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Authors and Affiliations

  1. Division of Hematology & Oncology and Comprehensive Cancer Center, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA

    Michelle L. Wynn, Megan Egbert, Jungsoo Chang, Zhi-Fen Wu & Sofia D. Meravjer

  2. Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA

    Michelle L. Wynn, Megan Egbert, Nikita Consul & Santiago Schnell

  3. Department of Computational Medicine & Bioinformatics, and Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI, USA

    Michelle L. Wynn & Santiago Schnell

  4. Columbia University College of Physicians & Surgeons, New York, NY, USA

    Nikita Consul

Authors
  1. Michelle L. Wynn
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  2. Megan Egbert
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  3. Nikita Consul
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  4. Jungsoo Chang
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  5. Zhi-Fen Wu
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  6. Sofia D. Meravjer
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  7. Santiago Schnell
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Corresponding author

Correspondence to Santiago Schnell.

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Wynn, M.L., Egbert, M., Consul, N. et al. Inferring Intracellular Signal Transduction Circuitry from Molecular Perturbation Experiments. Bull Math Biol 80, 1310–1344 (2018). https://doi.org/10.1007/s11538-017-0270-9

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  • DOI: https://doi.org/10.1007/s11538-017-0270-9

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